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Datatonic

Enterprise cloud data and AI consulting

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Expertise in Python and/or Java, with proficiency in SQL.
  • At least five years of experience designing and building scalable data solutions.
  • Hands-on experience with ETL tools, Hadoop-based technologies such as Spark, and data processing frameworks such as Beam or Flink.
  • Ability to write tested, resilient, and well-documented code.
  • Experience building and maintaining cloud infrastructure; GCP or AWS experience is a plus.
  • Experience in line management and mentoring engineers, helping grow the team's technical capabilities.
  • Ability to take ownership and drive projects from concept to completion.

Responsibilities

  • Design, develop, and optimize robust data pipelines that make data accessible for visualization and machine learning applications.
  • Use cloud-based platforms and big data processing tools to create scalable and efficient solutions.
  • Work with data scientists, ML engineers, and analysts in an agile environment to deliver data-driven solutions.
  • Integrate data solutions using Google Cloud Platform, dbt, and Looker.
  • Architect, maintain, and troubleshoot cloud-based infrastructure to ensure high availability and performance.
  • Guide and mentor engineers, supporting their professional development and promoting data engineering best practices.

Desired Qualifications

  • Previous experience working in a start-up or scale-up environment.
  • Experience with Linux scripting and command-line tools.
  • Experience building scalable REST APIs using Python or similar technologies.
  • Knowledge or experience in machine learning, data mining, statistics, and visualization.
  • Prior experience in a client-facing position.
  • Experience contributing to open-source projects.

About the Company

Datatonic

Enterprise cloud data and AI consulting

Datatonic is a specialised data analytics and AI consultancy focused on helping enterprise clients harness data on Google Cloud. It builds and manages data platforms, migrates legacy systems to the cloud, and develops MLOps pipelines and Generative AI applications to improve decision-making and operational efficiency. The firm differentiates itself through deep Google Cloud expertise (a 10-time Google Cloud Partner of the Year), end-to-end services (cloud architecture, data analytics, AI/ML, and training), and a strategic growth path that includes acquisitions (Montreal Analytics, Syntio) to expand data engineering and North American presence. Its goal is to enable enterprises across sectors to unlock the value of their data, deploy AI solutions quickly, and continuously improve performance through analytics and AI capabilities.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2013

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